Location: Temperate Tree Fruit and Vegetable Research
Project Number: 2092-21220-003-033-A
Project Type: Cooperative Agreement
Start Date: Apr 1, 2025
End Date: Jul 31, 2027
Objective:
OBJECTIVE 1. Determine beet leafhopper-transmitted pathogen prevalence in beet leafhoppers collected near vegetable and seed crops in the Columbia Basin, with a focus on new tomato field operations.
OBJECTIVE 2: Assess beet leafhopper population dynamics and pathogen prevalence in beet leafhoppers and crop hosts in a small plot study.
OBJECTIVE 3: Examine abiotic factors in relation to beet leafhopper abundance and pathogen prevalence data across the Columbia Basin to generate population and pathogen forecast models.
Approach:
Objective 1. Two sticky traps, replaced weekly, will be placed near each potato, tomato, or other vegetable/seed field throughout the growing season. Beet leafhoppers (n=10 per trap per week) will be tested for beet leafhopper pathogens using our high-throughput assays. Beet leafhopper populations and pathogen prevalence will be updated weekly to the Washington State University Decision Aid System to provide growers with near real-time data for incorporation into integrated pest management programs.
Objective 2. A small plot trial will be conducted at the USDA-ARS Moxee Research farm including four replicates of six different crops (carrot, green bean, potato, radish, tomato, and sugar beet), planted in a randomized complete block design. Beet leafhopper specimens will be collected bi-weekly from the middle 50 feet of each 100-foot crop replicate and isolated by sorting and visual identification. Prior to plant senescence, plant tissue will be collected from 50 plants grown within the middle 50 feet of each crop replicate. Insect and plant tissue will be subjected to nucleic acid extraction and pathogen detection. In-season beet leafhopper population dynamics and pathogen prevalence will be assessed.
Objective 3. To assess the role of abiotic factors on beet leafhopper pathogen prevalence in the Columbia Basin, abiotic variables (preceding fall/winter and yearly summer temperatures, precipitation, elevation at each collection site, etc.) from 2021, 2022, and 2023, will be paired with beet leafhopper population and pathogen prevalence data. As population and pathogen data is obtained from additional years, this information will be included to refine any forecasting model that is developed from this information. These models will be disseminated through research and extension publications, regional conferences and online on the Washington State University Decision Aid System website.
